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Main Authors: Koenker, Roger, Gu, Jiaying
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.00704
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author Koenker, Roger
Gu, Jiaying
author_facet Koenker, Roger
Gu, Jiaying
contents Two strategies are explored for robustifying classical denoising procedures for the Gaussian sequence model. First, the Hodges and Lehmann (1952) restricted Bayes approach is used to reduce sensitivity to the specification of the initial prior distribution. Second, alternatives to the Gaussian noise assumption are explored. In both cases proposals of Huber (1964) and Mallows (1978) play a crucial role.
format Preprint
id arxiv_https___arxiv_org_abs_2603_00704
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Robustifying Empirical Bayes
Koenker, Roger
Gu, Jiaying
Methodology
Econometrics
Two strategies are explored for robustifying classical denoising procedures for the Gaussian sequence model. First, the Hodges and Lehmann (1952) restricted Bayes approach is used to reduce sensitivity to the specification of the initial prior distribution. Second, alternatives to the Gaussian noise assumption are explored. In both cases proposals of Huber (1964) and Mallows (1978) play a crucial role.
title Robustifying Empirical Bayes
topic Methodology
Econometrics
url https://arxiv.org/abs/2603.00704